Computational and neural mechanisms of human safety decisions

This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) program with support from SBE's Decision, Risk, and Management Sciences (DRMS) and Cognitive Neurosciences (CogNeuro) programs. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government.

SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal.

Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Dean Mobbs at California Institute of Technology, this postdoctoral fellowship award supports an early career scientist investigating the mechanisms of human safety decisions.

Every day humans engage in complex decision processes that promote survival by acquiring protection. Protection acquisition varies from simple decisions such as taking vitamins to ward off illness, to more complex behaviors such as building and training armies to defend against future threats. Despite observing numerous and diverse examples of safety decisions across individuals, scientists have not identified the cognitive and neural systems that promote protection acquisition.

It is important to understand how humans achieve the goal of protecting ourselves because acquiring protection allows us to maintain safety and spend resources to engage in other important pursuits like creativity and cooperation. The purpose of this research is to contribute to a unified model of how the brain supports adaptive safety decisions. Additionally, a better understanding of how humans achieve safety has the potential to improve treatments for psychological disorders, including anxiety, which is characterized by an inability to recognize safety.

This proposal will make important basic science contributions to theories of decision making and will inform future efforts to promote healthy decision making in the face of threat. This proposal will examine the computational decision control systems that support adaptive safety acquisition, reward acquisition, and threat avoidance. This work will achieve three main aims (1) define computational mechanisms underpinning safety decision, (2) identify neural circuitry supporting safety acquisition, (3) compare neural substrates to safety acquisition to classical conditioning.

In part (1), this proposal will identify the extent to which safety decisions are associated with reflexive model-free learning and more effortful goal-directed model-based learning. By comparing decisions across the valence spectrum from positive reward to negative threat, this research will test how motivation shapes use of decision control systems.

In part (2), computational models of learning will be paired with neuroimaging to advance understanding of how the brain supports adaptive safety decisions. Identifying neurocircuitry involved in safety decisions is a necessary precursor to treating anxiety disorders characterized by maladaptive safety decisions. In part (3), safety acquisition decisions will be compared with safety learning in the absence of decision making via classical condition to lay the groundwork for a comprehensive model of safety processing.

By combining these methods, this research has the potential to identify overlapping and distinct neural systems involved in recognizing safety and making proactive decisions to acquire safety.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.